AWS Machine Learning Services

Main Article Content

Pratibha Sharma
Manisha Joshi

Abstract

As organizations seek to harness the power of machine learning (ML) to enhance decision-making and innovation, cloud platforms play a key role in democratizing access to ML capabilities types of This paper examines the state of machine learning services provided by Amazon Web Services (AWS). gunmaker etc. It provides an overview of the core AWS ML applications, exploring their use, use cases, and integration across applications Through a combination of textbooks, AWS documentation, and real-world case studies, this review aims to build highlights the transformational potential of AWS machine learning services , providing insights into the current state of technology, upcoming trends, and implications for various industries Industry. The abstract includes the abstract of AWS Machine Learning Services, which is a brief introduction to the detailed analysis of a full research paper.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Article Details

How to Cite
Sharma, P. ., & Joshi, M. . (2019). AWS Machine Learning Services. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(2), 1171–1174. https://doi.org/10.61841/turcomat.v10i2.14390
Section
Research Articles

References

GUJARATI, A., ELNIKETY, S., HE, Y., MCKINLEY, K. S., AND BRANDENBURG, B. B. Swayam:

distributed autoscaling to meet slas of machine learning inference services with resource efficiency. In Proceedings

of ACM/IFIP/USENIX Middleware Conference (2017), ACM, pp. 109–120.

HAN, R., GHANEM, M. M., GUO, L., GUO, Y., AND OSMOND, M. Enabling cost-aware and adaptive

elasticity of multi-tier cloud applications. Future Generation Computer Systems 32 (2014), 82–98.

HARLAP, A., TUMANOV, A., CHUNG, A., GANGER, G. R., AND GIBBONS, P. B. Proteus: Agile ML

elasticity through tiered reliability in dynamic resource markets. In Proceedings of ACM EuroSys (2017).

HE, K., ZHANG, X., REN, S., AND SUN, J. Deep residual learning for image recognition. In Proceedings of

IEEE CVPR (2016).

HE, X., SHENOY, P., SITARAMAN, R., AND IRWIN, D. Cutting the cost of hosting online services using

cloud spot markets. In Proceedings of the 24th International Symposium on High-Performance Parallel and

Distributed Computing (2015), ACM, pp. 207–218.

R. K. Kaushik Anjali and D. Sharma, "Analyzing the Effect of Partial Shading on Performance of Grid

Connected Solar PV System", 2018 3rd International Conference and Workshops on Recent Advances and

Innovations in Engineering (ICRAIE), pp. 1-4, 2018

HUNT, P., KONAR, M., JUNQUEIRA, F. P., AND REED, B. Zookeeper: Wait-free coordination for internetscale systems. In Proceedings of USENIX ATC (2010).

KLEIN, G., KIM, Y., DENG, Y., SENELLART, J., AND RUSH, A. M. Opennmt: Open-source toolkit for

neural machine translation. arXiv preprint arXiv:1701.02810 (2017).